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Lee Atchison is an author and recognized thought leader in cloud computing and application modernization with more than three decades of experience, working at modern application organizations such as Amazon, AWS, and New Relic. Lee is widely quoted in many publications and has been a featured speaker across the globe. Lee’s most recent book is Architecting for Scale (O’Reilly Media). https://leeatchison.com

lambda, deployments, AWS Lambda FaaS Serverless Computing vs. Containers

Is AWS Lambda a Replacement For Servers?

Function-as-a-service is great for certain classes of problems, but for some types of computation, FaaS is, quite simply, a bad fit ...
Lee Atchison | October 31, 2023 | AWS Lambda, cloud native computing, FaaS, function-as-a-service, serverless, servers
complexity Kubernetes Kafka

How to Avoid Cloud-Native Complexity

The more choices users have in your cloud-native application, the more complex it gets. Uncontrolled complexity, like entropy, always increases ...
Lee Atchison | October 24, 2023 | application, application development, aws, cloud native
DNS cloud-native application data mainframes containers

Are You Giving DNS the Respect it Deserves?

The backbone of all modern, cloud-native applications is DNS, and ignoring it can kill your business. Are you giving it the respect it deserves? ...
Lee Atchison | October 17, 2023 | cloud-native applications, cloud-native architecture, DNS, networking
Should Cloud-Native Applications Use a Monorepo?

Should Cloud-Native Applications Use a Monorepo?

Does every system or component in a cloud-native app need its own code repository? Or can they all share a single code repository? ...
Lee Atchison | October 10, 2023 | cloud native, cloud-native applications, code repository, Git, monorepo
Java Veeam data AppSec technical debt

Scheduled Maintenance? That’s Another Way of Saying Technical Debt

No truly modern, cloud-native application should require downtime to perform a product upgrade or other routine maintenance ...
Lee Atchison | October 3, 2023 | cloud native, cloud-native applications, downtime, modernization, technical debt
SRE, autoscaling, Tailscale, Kubernetes, argo cd, Kubernetes v1.33,  AI, Nelm, Kubernetes, architecture, , architecture, Rackspace, GPUs, Kubernetes, Solo.io Kubernetes cloud foundry keptn cloud-native automation

How to Build and Manage a Cloud Center of Excellence

For organizations devoted to harnessing the full potential of cloud-native applications, the establishment of a Cloud Center of Excellence (CCoE) is a common first step ...
Lee Atchison | September 26, 2023 | CCoE, cloud center of excellence, cloud native, education, training
Seccomp downtime Kubernetes

Why Maintenance Windows Don’t Work for Cloud-Native Apps

Whether planned and expected or unplanned and unexpected, downtime is downtime ...
Lee Atchison | September 19, 2023 | cloud-native applications, downtime, maintenance, upgrades
APIs, microservices, Fermyon, Wasm, Gerrit, systems, services, microservices, JFrog, AI, microservices, tools, GitOps MicroK8s Red Hat Kogito D2iQ

Stop Turning Success Into Failure With Microservices

MIcroservices can help you avoid business failure because of huge, monolithic application architecture ...
Lee Atchison | September 12, 2023 | application architecture, application development, cloud native, microservices
metrics, agents, ai, cloud-native, cloud native, project, istio, ambient, architecture, modules, cloud native, CCoE Kubernetes Virtana CrowdStrike cloud native

Can a Cloud Center of Excellence Help You Become Cloud Native?

A cloud center of excellence (CCoE) can be an extremely valuable asset for an organization looking to build and migrate cloud-native applications ...
Lee Atchison | September 5, 2023 | cloud center of excellence, cloud computing, cloud-native architecture, standardization
principle Cloudera cloud-native IBM Cloud Pak

Cloud Isn’t That Simple Anymore: Polycloud Vs. Sky Computing

Multi-cloud—a strategy for employing multiple cloud providers—is a common strategy used by cloud-native applications. Many applications make use of both Amazon Web Services (AWS) and another cloud provider, such as Google Cloud ...
Lee Atchison | August 29, 2023 | cloud native application development, cloud provider, multi-cloud
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AppSec in 2026: Security at Machine Speed — or Not at All
18 May 2026
AppSec in 2026: Security at Machine Speed — or Not at All
Analyze Terraform using Agentic GenAI workflows
14 May 2026
Analyze Terraform using Agentic GenAI workflows
Multi-Million-Dollar Lessons: What FinOps Maturity Actually Looks Like
14 May 2026
Multi-Million-Dollar Lessons: What FinOps Maturity Actually Looks Like
From Prompt to Exploit: How LLMs Are Changing API Attacks
13 May 2026
From Prompt to Exploit: How LLMs Are Changing API Attacks
Data is the Differentiator for Exposure Management
6 May 2026
Data is the Differentiator for Exposure Management
The Context Engine: Why Consolidation is the Natural Future of AppSec
5 May 2026
The Context Engine: Why Consolidation is the Natural Future of AppSec

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ThreatHunter.ai Halts Hundreds of Attacks in the past 48 hours: Combating Ransomware and Nation-State Cyber Threats Head-On

ThreatHunter.ai Halts Hundreds of Attacks in the past 48 hours: Combating Ransomware and Nation-State Cyber Threats Head-On

Deloitte Partners with Memcyco to Combat ATO and Other Online Attacks with Real-Time Digital Impersonation Protection Solutions

Deloitte Partners with Memcyco to Combat ATO and Other Online Attacks with Real-Time Digital Impersonation Protection Solutions

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The State of Incident Response and Observability

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Which of the following best describes your involvement with observability or incident response in your organization?(Required)
What are your biggest pain points in incident response today? (Select up to 4)(Required)
Which of the following best describes your team’s current use of AI in observability and operations?(Required)
When your team uses or has evaluated AI-assisted observability, how well does the AI include the full context of an incident—including relationships across services, infrastructure, recent changes, and team knowledge?(Required)
If an AI agent could investigate incidents and identify root cause in minutes, what would you most want it to do next?(Required)
What are the two biggest risks to your production environment today? (Select no more than 2)(Required)
What percentage of your team’s operational time is spent on reactive incident response versus proactive prevention and improvement?(Required)

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